Research into artificial intelligence (AI) has made tremendous progress over the past
decade. In particular, the AI-powered analysis of images and signals has reached human …

Echocardiography plays a crucial role in the diagnosis and management of cardiovascular
disease. However, interpretation remains largely reliant on the subjective expertise of the …

Aims We tested the hypothesis that a machine learning (ML) algorithm utilizing both complex
echocardiographic data and clinical parameters could be used to phenogroup a heart failure …

Heart failure (HF) is a heterogeneous syndrome affecting more than 60 million individuals
globally. Despite recent advancements in understanding of the pathophysiology of HF, many …

Background: Current diagnosis of heart failure with preserved ejection fraction (HFpEF) is
suboptimal. We tested the hypothesis that comprehensive machine learning (ML) of left …

Background Stress testing helps diagnose heart failure with preserved ejection fraction
(HFpEF), but there are no established criteria for quantifying left ventricular (LV) functional …

An older population with an increased prevalence of cardiovascular disease and an aging
workforce are engendering a state of healthcare crisis in cardiology. 1 Most cardiologists …

Introduction Artificial intelligence (AI) describes the use of computational techniques to
mimic human intelligence. In healthcare, this typically involves large medical datasets being …

A higher proportion of patients with heart failure have benefitted from a wide and expanding
variety of sensor-enabled implantable devices than any other patient group. These patients …

Aims We investigated left ventricular (LV) remodeling, mechanics, systolic and diastolic
function, combined with clinical characteristics and heart-failure treatment in association to …